mcpField
K
kardashev-mcp

kardashev-mcp

Local
kardashevlabs.orgData & Analytics0Updated 6w ago
RepositoryVisit website

About kardashev-mcp

kardashev-mcp exposes US electricity-grid data from Kardashev Labs for agents and other MCP clients. Its tools cover live market and grid measures, interconnection queues, ERCOT large loads, and a public RT−DA spread forecast track record; no API key is required.

Key features

  1. 01Live LMP and carbon-intensity data
  2. 02Grid load and near-term forecasts
  3. 03Curtailment and interconnection queues
  4. 04ERCOT large-load snapshots
  5. 05RT−DA spread forecasts and track record

Use cases

  1. 01Reviewing live US grid conditions
  2. 02Analyzing electricity prices and carbon intensity
  3. 03Inspecting interconnection queues and ERCOT loads
  4. 04Evaluating RT−DA spread forecast performance

MCP support

Provides MCP tools for querying public Kardashev Labs US grid data, including prices, carbon intensity, load, queues, and forecasts. No API key is required.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "kardashev-lab-kardashev": {
      "command": "npx",
      "args": [
        "-y",
        "kardashev-mcp"
      ]
    }
  }
}
Run commandnpx -y kardashev-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmkardashev-mcp0.1.0

Tools

11

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
include_basbooleanNoInclude smaller balancing authorities. Default false.

Details

From the project README

kardashev-mcp

npm

MCP server for Kardashev Labs US grid data. Gives agents live LMP, carbon intensity, load, curtailment, interconnection queues, ERCOT large loads, and the public RT−DA spread forecast track record. No API key required.

Data comes from the public API at data.kardashevlabs.org.

Install

npx -y kardashev-mcp
Cursor (~/.cursor/mcp.json)
{
  "mcpServers": {
    "kardashev": {
      "command": "npx",
      "args": ["-y", "kardashev-mcp"]
    }
  }
}
Claude Code
claude mcp add kardashev -- npx -y kardashev-mcp

Tools

ToolWhat it returns
list_isosCovered ISOs/RTOs and live ingest status
get_fuel_mixGeneration by fuel type (MW)
get_carbonCarbon intensity (lbs CO₂/MWh)
get_lmpLocational marginal prices (RT/DA)
get_loadActual grid load (MW)
get_load_forecastNear-term load forecast
get_curtailmentSolar/wind curtailment
get_queueInterconnection queue projects
get_large_loadERCOT large-load interconnection snapshot
get_spread_forecastLive ERCOT RT−DA spread forecast (issued before delivery)
get_forecast_track_recordScored public track record for the spread models

Row-returning tools default to limit=50 (hard max 500) so agents stay within context budgets.

Optional env

VariableDefaultPurpose
KARDASHEV_BASE_URLhttps://data.kardashevlabs.orgOverride API base (local data plane)
KARDASHEV_TIMEOUT_MS30000Per-request timeout

Develop

npm install
npm run build
npm start                 # stdio
npm run inspect           # MCP Inspector

Links

License

MIT

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.